R. Debruyne and C. Bessiere. From restricted path consistency to max-restricted path consistency. In Proceedings CP'97, pages 312--326, Linz, Austria, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... 10 100i no [DF,IR,LV] 20] B h20; 4i p2 = 0:125 h150; 3i p2 = 0:222 h20 75; 6i, h20; 10i no CP 97 [IPG,JLU] 29] D h10; 10i no [IR,DF] 48] B h100; 8i no [DS,ECF] 50] B h20; 20i, h40; 20i no [BMS,SAG] 54] B h10; 10i no [PG,JKH] 21] B h50; 10i, h100; 15i, h250; 25i, no [RD,CB] [10] B h100; 20i no [IPG,EM, PP, PS, TW] 23] B h20 70; 10i no IJCAI 97 [RD, CB] 11] B h20; 10i no Table 1. Parameters and models used in some previous studies of random constraint satisfaction problems. The nal column details studies in which model B or C was used and p2 1=m. In the limit, ....

R. Debruyne and C. Bessiere. From restricted path consistency to max-restricted path consistency. In G. Smolka, editor, Proceedings of Third International Conference on Principles and Practice of Constraint Programming (CP97), pages 312{

.... 100i no [DF,IR,LV] 20] B h20; 4i p2 = 0:125 h150; 3i p2 = 0:222 h20 Gamma 75; 6i, h20; 10i no CP 97 [IPG,JLU] 29] D h10; 10i no [IR,DF] 48] B h100; 8i no [DS,ECF] 50] B h20; 20i, h40; 20i no [BMS,SAG] 54] B h10; 10i no [PG,JKH] 21] B h50; 10i, h100; 15i, h250; 25i, no [RD,CB] [10] B h100; 20i no [IPG,EM, PP, PS, TW] 23] B h20 Gamma 70; 10i no IJCAI 97 [RD, CB] 11] B h20; 10i no Table 1. Parameters and models used in some previous studies of random constraint satisfaction problems. The final column details studies in which model B or C was used and p2 1=m. In the ....

R. Debruyne and C. Bessi`ere. From restricted path consistency to max-restricted path consistency. In G. Smolka, editor, Proceedings of Third International Conference on Principles and Practice of Constraint Programming (CP97), pages 312--

.... Gamma 100i no [DF,IR,LV] 19] B h20; 4i p2 = 0:125 h150; 3i p2 = 0:222 h20 Gamma 75;6i, h20; 10i no CP 97 [IPG,JLU] 27] D h10; 10i no [IR,DF] 45] B h100; 8i no [DS,ECF] 47] B h20; 20i, h40; 20i no [BMS,SAG] 50] B h10; 10i no [PG,JKH] 20] B h50; 10i, h100; 15i, h250; 25i, no [RD,CB] [10] B h100; 20i no [IPG,EM, PP, PS, TW] 22] B h20 Gamma 70;10i no IJCAI 97 [RD, CB] 11] B h20; 10i no Table 2. Parameters and models used in some previous studies of random constraint satisfaction problems. bound on the probability of a flawed variable, Prfproblem has a flawed variableg n(1 ....

R. Debruyne and C. Bessi`ere. From restricted path consistency to max-restricted path consistency. In G. Smolka, editor, Proceedings of Third International Conference on Principles and Practice of Constraint Programming (CP97), pages 312--

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R. Debruyne and C. Bessiere. From restricted path consistency to max-restricted path consistency. In Proceedings CP'97, pages 312--326, Linz, Austria, 1997.

No context found.

R. Debruyne and C. Bessiere. From restricted path consistency to maxrestricted path consistency. In Proceedings CP'97, pages 312--326, Linz, Austria, 1997.

No context found.

Debruyne, R., Bessi`ere, C.: From Restricted Path Consistency to Max-Restricted Path Consistency. Technical Report 97036, Montpellier, France (1997)

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R. Debruyne and C. Bessiere. From restricted path consistency to max-restricted path consistency. In Proceedings CP'97, pages 312--326, Linz, Austria, 1997.

....on using explanations for intervals has been done for numerical csp [14] Any constraint solver able to provide explanations can be integrated in dbt in the same way we previously described it for arc consistency. It would be the case for high level of stronger consistencies in binary csp (see [9, 8] for high level consistencies) or for non binary constraints. mac dbt can also be used for different kinds of problems, for example to drastically improve the resolution of scheduling problems [13] 12 15, 10, 43 problems 0 2 4 6 8 10 12 10 20 30 40 50 60 70 80 90 tightness cpu ....

Romuald Debruyne and Christian Bessi`ere. From restricted path consistency to max-restricted path consistency. In CP'97, pages 312--326, Linz, Austria, October 1997.

....A good illustration is that MAC outperforms forward checking on hard problems. The question is, Is there a local consistency that outperforms arc consistency (AC) on very hard CNs . To give a rst answer, some comparisons between the local consistencies more pruningful than AC have been carried out [3][4] considering both pruning and time efciencies. From that work, retricted path consistency (RPC, 1] and Max RPC seem be victorious. Path inverse consistency was indeed more expensive than Max RPC while not pruning far more than RPC which is weaker and cheaper. PIC1, the PIC algorithm used for ....

....[1] and Max RPC seem be victorious. Path inverse consistency was indeed more expensive than Max RPC while not pruning far more than RPC which is weaker and cheaper. PIC1, the PIC algorithm used for the comparison is in O(en 2 d 4 ) when RPC2 and MaxRPC1 (the Max RPC algorithm proposed in [3]) are in O(ed 2 cd 2 ) 2 1 Ecole des Mines de Nantes, 4, rue Alfred Kastler, La Chantrerie, 44307 Nantes cedex 03 France, email: romuald.debruyne emn.fr 2 c is the number of 3 cliques in the network and O(ed 2 cd 3 ) respectively. But PIC is a recent ltering technique and has ....

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R. Debruyne and C. Bessi`ere, From Restricted Path Consistency to MaxRestricted Path Consistency, 312326, In CP-97, Linz, Austria, 1997.

....path consistency and Max restricted path consistency. We propose a new class of local consistencies called singleton consistencies. We also show a property of path inverse consistency that can be used to have an optimal worst case time complexity in a path inverse consistency algorithm (Debruyne, 2000). Arc consistency The most widely used local consistency is arc consistency. It is based on the notion of support. A value is viable as long as it has at least one compatible value in the domain of each neighboring variable. An AC algorithm has to remove the values that have no support on a ....

.... O(en ed 2 cd 2 ) #) O(ed cd) Max RPC1 (Debruyne Bessiere, 1997a) O(en ed 2 cd 3 ) #) O(ed cd) PC5 (Singh, 1995) O(n 3 d 3 ) #) O(n 3 d 2 ) PC8 (Chmeiss Jegou, 1996) O(n 3 d 4 ) O(n 2 d) 2 PIC1 (Freuder Elfe, 1996) O(en 2 d 4 ) O(n) PIC2 (Debruyne, 2000) O(en ed 2 cd 3 ) #) O(ed cd) NIC1 (Freuder Elfe, 1996) O(g 2 (n ed)d g 1 ) O(n) SAC1 (Debruyne Bessiere, 1997b) O(en 2 d 4 ) O(ed) SRPC1 (Debruyne Bessiere, 1997b) O(en n 2 (e c)d 4 ) O(ed cd) #) optimal worst case time complexity. Table 1: The most ....

[Article contains additional citation context not shown here]

Debruyne, R., & Bessiere, C. (1997a). From restricted path consistency to max-restricted path consistency. In Proceedings of CP-97, Linz, Austria, pp. 312--326.

....path consistency and Max restricted path consistency. We propose a new class of local consistencies called singleton consistencies. We also show a property of path inverse consistency that can be used to have an optimal worst case time complexity in a path inverse consistency algorithm (Debruyne, 2000). Arc consistency The most widely used local consistency is arc consistency. It is based on the notion of support. A value is viable as long as it has at least one compatible value in the domain of each neighboring variable. An AC algorithm has to remove the values that have no support on a ....

.... O(en ed 2 cd 2 ) O(ed cd) Max RPC1 (Debruyne Bessi ere, 1997a) O(en ed 2 cd 3 ) O(ed cd) PC5 (Singh, 1995) O(n 3 d 3 ) O(n 3 d 2 ) PC8 (Chmeiss J egou, 1996) O(n 3 d 4 ) O(n 2 d) 2 PIC1 (Freuder Elfe, 1996) O(en 2 d 4 ) O(n) PIC2 (Debruyne, 2000) O(en ed 2 cd 3 ) O(ed cd) NIC1 (Freuder Elfe, 1996) O(g 2 (n ed)d g 1 ) O(n) SAC1 (Debruyne Bessi ere, 1997b) O(en 2 d 4 ) O(ed) SRPC1 (Debruyne Bessi ere, 1997b) O(en n 2 (e c)d 4 ) O(ed cd) optimal worst case time complexity. Table 1: The most ....

[Article contains additional citation context not shown here]

Debruyne, R., & Bessi`ere, C. (1997a). From restricted path consistency to max-restricted path consistency. In Proceedings of CP-97, Linz, Austria, pp. 312--326.

....A and B if A and B are incomparable w.r.t. the stronger relation. A proof of the relations presented in fig.2 can be found in [6] Especially, if A is not stronger than B (B is strictly stronger than A or A and B are incomparable) a CN in which A holds and B does not hold can be found in [6] and [4]. Some local consistencies are incomparable with respect to the strong relation. Moreover, fig.2 gives some qualitative properties, but no quantitative information. It can be interesting to determine if a local consistency can detect much more inconsistent values than another local ....

Debruyne, R., Bessi`ere, C.: From Restricted Path Consistency to Max-Restricted Path Consistency. Technical Report 97036, Montpellier, France (1997)

No context found.

R. Debruyne and C. Bessiere. From restricted path consistency to maxrestricted path consistency. In Proceedings of CP-97, pages 312-326, 1997.

No context found.

R. Debruyne and C. Bessire. "From restricted path consistency to max-restricted path consistency." Proc. of the International Conference on Principles and Practice of Constraint Programming (CP'97).

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R. Debruyne, C. Bessiere, From Restricted Path Consistency to Max-Restricted Path Consistency, Proc. Principles and Practice of Constraint Programming, 312--326, 1997.

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